The long term goal of this proposal is to improve patient survival by providing the neurosurgeon with the advanced image-guidance technology necessary for optimal intraoperative decision-making during removal of malignant gliomas (MGs). It merges Dartmouth's long-standing interest and expertise in developing image-guidance for open cranial surgeries with the University of Toronto's depth in realizing state-of-the-art instrumentation and procedures for monitoring tissue fluorescence to create an unprecedented degree of integration and synthesis of conventional volumetric imaging (obtained preoperatively) with novel surface/subsurface fluorescence (obtained intraoperatively) for guidance during brain tumor resection. The proposed research is structured to identify the optimal procedural paradigm for neurosurgical resection of MGs by exploring coregistered intraoperative fluorescence imaging (Fl) as an augmentation of preoperative MR guided resection (MRGR) in the late stages of surgery. Integration of new optical technology, namely, fluorescence imaging that is quantitative (qFI) and depth-resolved (dFI) into the operative setting is also planned which will deliver new information not previously acquired or evaluated in prior neurosurgical FIGR studies reported in the recent literature. The expectation is that co-registration of these new qFI and dFI signals with pMR will augment the neurosurgeon's ability to identify resection margins with higher probability of tumor control/cure at a lower incidence of functional impairment secondary to surgery for a broader range of histological MG grades than has been previously possible. The specific aims that underpin the proposal effort are to: (1) Develop through-(operating)-microscope (TM) Fl coregistered with pMR and use this system to quantify (i) the degree of spatial correlation between Fl signatures and pMR image features and (ii) Fl signal strength recorded in vivo relative to fluorophore concentration measured in biopsy specimens as a function of histological grade in a clinical series of MG resections. (2) Develop qFI and dFI algorithms for augmented Fl and implement these concepts in a novel free-standing (FS) platform for preclinical FIGR evaluation. (3) Validate the qFI and dFI additions in phantom and animal studies culminating in a preclinical evaluation trial that identifies and defines the optimal design characteristics and performance expectations for an advanced TM realization. (4) Implement an advanced TM system (based on Aim #3 data) coregistered with pMR and complete a clinical series of cases which address the efficacy of FIGR+MRGR versus MRGR alone in terms of completeness of resection evaluated intra- and post-operatively across histological MG grades in order to demonstrate improvements in surgical accuracy for an expanded range of histologies with the quantitative FIGR+MRGR approach.